Epigenome editing provides an opportunity to reverse aberrant epigenetic drivers of diseases such as cancer where epigenetic change drives tumour evolution and determines treatment success. Adapting CRISPR/Cas9 genome editing to the clinic requires the integration of large, heterogeneous biological data sets into a unified in silico cellular model suitable for vector design and analysis. We propose to integrate genome, epigenome, and transcriptome sequencing for designing epigenome modifying CRISPR (EpiCRISPR) vectors. Our software platform will map epigenetic changes associated with disease states and design EpiCRISPR libraries targeting gene regulatory elements associated with an altered epigenetic landscape to generate novel epigenome editing treatment approaches. We will utilise the drug-resistance in ovarian cancer as a test case, where clinically relevant genomic and epigenomic datasets have already been generated and there is a clinical need to improve patient outcome by overcoming drug resistance. We anticipate a tool of this caliber will allow for unparalleled insight into the function of cellular mechanisms and thus hugely impact translational omics research.

Artificial genes made from synthetic DNA are vital to new drug research in oncology, infectious diseases and regenerative medicine, as well as the production of high-value chemicals, biofuels, and many other industrial products. Current manual gene assembly methods are laborious, time-consuming, and typically yield only 25 error-free genes per 100 attempts. Although external contractors can absorb the cost of high error rates, these services are expensive, have long turn-around times, and are all based outside the UK. Researchers currently tolerate these problems yet significant time, effort and resources are wasted on making and re-making DNA instead of the actual running of new and creative experiments. This limits the Life Sciences sector and all related areas of the economy. Our objective is to develop and demonstrate a system that will provide users with optimised in-house gene assembly methods at accuracy 100-fold greater than that achieved today. We aim to push typical success rates up to 98 error-free genes per 100 attempts. We intend to accomplish this by directly addressing the primary sources of gene assembly error: poor gene design, poor assembly methodology design, operational error and the use of error-prone starting materials. This system will be built on a robust and experimentally proven bioinformatics platform, capable of optimising DNA assembly methods based on the user’s internal inventory of existing DNA samples, as well as external inventories available from collaborators, commercial suppliers or unknown potential partners. Similar to a travel website that finds the best fares, we are developing technology that consistently finds the best way to build any molecule of DNA. The result of this work will be the acceleration of the “design-build-test” cycle in biotechnology R&D and will support the UK’s development of a “bio-economy”.

Desktop Genetics is developing a rapid prototyping solution for biotechnology. Researchers in the industry require synthetic genes to engineer new biopharmaceutical drugs, high value chemicals and biofuels, but lack the tools to effectively make these genes. Constrained to buying them from service providers, they waste resources waiting for these to arrive, thus limiting their research.DeskGen's solution allows scientists to make genes reliably and rapidly, in-house. To ensure that this device provides scientists with the most seamless experience, and to ensure full integration across other pieces of laboratory equipment, DeskGen has partnered with design advisers to plan the development of a truly innovative instrument for Life Sciences laboratories. At DeskGen we are committed to providing the best solution for our customers and we believe this comes down to combining quality products with quality service and support.